| Citation: |
ZENG Yijin, WANG Minsheng, GUANG Xinjun, et al. Progress and prospects of Sinopec’s intelligent drilling technologies [J]. Petroleum Drilling Techniques, 2024, 52(5)：1−9. DOI: 10.11911/syztjs.2024081
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Intelligent drilling has functions such as self-perception, self-learning, self-decision-making, self-execution, and self-adaptation. It is expected to significantly improve drilling efficiency and reduce operating costs. In order to accelerate the development of intelligent drilling technologies, Sinopec has conducted research on key technologies such as automated drilling rigs and key equipment, geological parameter perception while drilling engineering, intelligent drilling analysis and decision-making, and intelligent drilling system integration in terms of real-time perception, intelligent decision-making, integrated control, and other aspects. Integration and demonstration applications have been carried out on site, achieving multi-objective collaborative optimization of application scenarios such as intelligent optimization of drilling parameters, intelligent warning of wellbore risks, and intelligent navigation of wellbore trajectories. The closed-loop control level of intelligent assistance and manual decision-making in consulting mode has been achieved, which effectively supports cost reduction and efficiency improvement in key oil and gas exploration and development fields. In order to better develop intelligent drilling technologies, based on the analysis of the current problems, the latest progress in the research on key technologies for intelligent drilling in Sinopec was summarized. It was proposed to further strengthen the research on key technologies such as fully automated drilling rigs and equipment, high-performance measurement and control systems, and digital twin decision-making systems, increase technological iteration and upgrading, and promote the transformation of intelligent drilling from consulting mode to semi-autonomous and autonomous control modes.
| [1] |
王敏生,光新军. 智能钻井技术现状与发展方向[J]. 石油学报,2020,41(4):505–512. doi: 10.7623/syxb202004013
WANG Minsheng, GUANG Xinjun. Status and development trends of intelligent drilling technology[J]. Acta Petrolei Sinica, 2020, 41(4): 505–512. doi: 10.7623/syxb202004013
|
| [2] |
王敏生. 沿钻柱测量技术及其发展方向[J]. 石油钻探技术,2022,50(4):52–58. doi: 10.11911/syztjs.2022001
WANG Minsheng. Along-string measuring technique and its development direction[J]. Petroleum Drilling Techniques, 2022, 50(4): 52–58. doi: 10.11911/syztjs.2022001
|
| [3] |
李根生,宋先知,祝兆鹏,等. 智能钻完井技术研究进展与前景展望[J]. 石油钻探技术,2023,51(4):35–47. doi: 10.11911/syztjs.2023040
LI Gensheng, SONG Xianzhi, ZHU Zhaopeng, et al. Research progress and the prospect of intelligent drilling and completion technologies[J]. Petroleum Drilling Techniques, 2023, 51(4): 35–47. doi: 10.11911/syztjs.2023040
|
| [4] |
张好林,杨传书,李昌盛,等. 钻井数字孪生系统设计与研发实践[J]. 石油钻探技术,2023,51(3):58–65. doi: 10.11911/syztjs.2023011
ZHANG Haolin, YANG Chuanshu, LI Changsheng, et al. Design and research practice of a drilling digital twin system[J]. Petroleum Drilling Techniques, 2023, 51(3): 58–65. doi: 10.11911/syztjs.2023011
|
| [5] |
杨传书,李昌盛,孙旭东,等. 人工智能钻井技术研究方法及其实践[J]. 石油钻探技术,2021,49(5):7–13. doi: 10.11911/syztjs.2020136
YANG Chuanshu, LI Changsheng, SUN Xudong, et al. Research method and practice of artificial intelligence drilling technology[J]. Petroleum Drilling Techniques, 2021, 49(5): 7–13. doi: 10.11911/syztjs.2020136
|
| [6] |
OLIVIER G. Using an E&P digital twin in well construction[EB/OL]. (2022-01-07)[2024-08-12]. https://www.halliburton.com/en/software/decisionspace-365-enterprise/decisionspace-365-well-construction.
|
| [7] |
BA S, IGNOVA M, MANTLE K, et al. Autonomous directional drilling planning and execution using an industry 4.0 platform[R]. SPE 204607, 2021.
|
| [8] |
LAI S W, NG J, EDDY A, et al. Large-scale deployment of a closed-loop drilling optimization system: implementation and field results[R]. SPE 199601, 2020.
|
| [9] |
李根生,宋先知,田守嶒. 智能钻井技术研究现状及发展趋势[J]. 石油钻探技术,2020,48(1):1–8. doi: 10.11911/syztjs.2020001
LI Gensheng, SONG Xianzhi, TIAN Shouceng. Intelligent drilling technology research status and development trends[J]. Petroleum Drilling Techniques, 2020, 48(1): 1–8. doi: 10.11911/syztjs.2020001
|
| [10] |
ZHANG Hongbao, ZENG Yijin, LIAO Lulu, et al. How to land modern data science in petroleum engineering[R]. SPE 205689, 2021.
|
| [11] |
MAYANI M G, BAYBOLOV T, ROMMETVEIT R, et al. Optimizing drilling wells and increasing the operation efficiency using digital twin technology[R]. SPE 199566, 2020.
|
| [12] |
KARPOV R, KOJADINOVIC K, KOKOTOVIC U, et al. Live digital twin improving drilling performance and providing foundation for the realtime data quality control[R]. SPE 216981, 2023.
|
| [13] |
蔡亚琳,柯式镇,康正明,等. 随钻电阻率成像测井在裂缝地层中的响应模拟[J]. 石油科学通报,2020,5(3):327–336. doi: 10.3969/j.issn.2096-1693.2020.03.028
CAI Yalin, KE Shizhen, KANG Zhengming, et al. Logging response simulation of a LWD resistivity imaging tool in fractured formations[J]. Petroleum Science Bulletin, 2020, 5(3): 327–336. doi: 10.3969/j.issn.2096-1693.2020.03.028
|
| [14] |
康正明,柯式镇,李新,等. 随钻电阻率成像测井仪定量评价地层界面探究[J]. 石油钻探技术,2020,48(4):124–130. doi: 10.11911/syztjs.2020087
KANG Zhengming, KE Shizhen, LI Xin, et al. Probe into quantitative stratigraphic interface evaluation using a resistivity imaging LWD tool[J]. Petroleum Drilling Techniques, 2020, 48(4): 124–130. doi: 10.11911/syztjs.2020087
|
| [15] |
李新,倪卫宁,米金泰,等. 一种基于非接触耦合原理的新型随钻微电阻率成像仪器[J]. 中国石油大学学报(自然科学版),2020,44(6):46–52. doi: 10.3969/j.issn.1673-5005.2020.06.006
LI Xin, NI Weining, MI Jintai, et al. A novel high-resolution resistivity imaging while drilling tool based on contactless coupling[J]. Journal of China University of Petroleum(Edition of Natural Science), 2020, 44(6): 46–52. doi: 10.3969/j.issn.1673-5005.2020.06.006
|
| [16] |
KANG Zhengming, LI Xin, NI Weining, et al. Using logging while drilling resistivity imaging data to quantitatively evaluate fracture aperture based on numerical simulation[J]. Journal of Geophysics and Engineering, 2021, 18(3): 317–327. doi: 10.1093/jge/gxab016
|
| [17] |
XU Wei, HUANG Hang, LI Xin, et al. Self-adaptive inversion method of electromagnetic-propagation resistivity logging while drilling data[J]. Applied Geophysics, 2022, 19(3): 343–352. doi: 10.1007/s11770-022-0939-1
|
| [18] |
ZHANG Hongbao, LU Baoping, YANG Shunhui, et al. A global drilling KPIs analysis system based on modern data science techniques[R]. SPE 203378, 2020.
|
| [19] |
ZHANG Hongbao, LU Baoping, LIAO Lulu, et al. Combining machine learning and classic drilling theories to improve rate of penetration prediction[R]. SPE 202202, 2021.
|
| [20] |
ZHANG Hongbao, ZENG Yijin, BAO Hongzhi, et al. Drilling and completion anomaly detection in daily reports by deep learning and natural language processing techniques[R]. URTEC 2020-2885, 2020.
|
| [21] |
ZHOU Fei, FAN Honghai, LU Baoping, et al. Application of DNN-TCN composite neural network in rate of penetration prediction[R]. SPE 209886, 2022.
|
| [22] |
BAI Kankan, FAN Honghai, ZHANG Hongbao, et al. Real time torque and drag analysis by combining of physical model and machine learning method[R]. URTEC 3723045, 2022.
|
| [23] |
ZHOU Fei, FAN Honghai, LIU Yuhan, et al. Application of XGBoost algorithm in rate of penetration prediction with accuracy[R]. IPTC 22100, 2022.
|
| [24] |
LU Baoping, XU Ting, HUANG Yuebin, et al. Applications of computer vision and deep learning in visual features extraction of drill bits[R]. IPTC 22624, 2022.
|
| [25] |
曾义金,李大奇,陈曾伟,等. 基于自然语言处理与大数据分析的漏失分析与诊断[J]. 石油钻探技术,2023,51(6):1–11. doi: 10.11911/syztjs.2023069
ZENG Yijin, LI Daqi, CHEN Zengwei, et al. Loss analysis and diagnosis based on natural language processing and big data analysis[J]. Petroleum Drilling Techniques, 2023, 51(6): 1–11. doi: 10.11911/syztjs.2023069
|
| [26] |
LU Baoping, YUAN Duo, WU Chao, et al. A drilling technology guided by well-seismic information integration[J]. Petroleum Exploration and Development, 2020, 47(6): 1325–1332. doi: 10.1016/S1876-3804(20)60140-4
|
| [27] |
JIANG Jun, LUO Fang, ZHANG Hongbao, et al. Adaptive multiexpert learning for lithology recognition[J]. SPE Journal, 2022, 27(6): 3802–3813. doi: 10.2118/209824-PA
|
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Supervisor：SINOPEC GROUP
Sponsor：Sinopec Research Institute of Petroleum Engineering
Serial Number：CN 11-1763/TE, ISSN 1001-0890
Chief Editor： WANG Minsheng
Supported by: Beijing Renhe Information Technology Co., Ltd. 
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